Pl-Quiver-Julia.ipynb

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   "source": [
    "using DataFrames, CSV, PlotlyJS, BenchmarkTools\n",
    "include(\"quiver.jl\")\n",
    "function get_quiver_plot(df)\n",
    "    X = vcat(df[!, :x], df[!, :x])\n",
    "    Y = vcat(df[!, :y], df[!, :y])\n",
    "\n",
    "    U = vcat(df[!, :u], map(x->-1*x, df[!, :u]))\n",
    "    V = vcat(df[!, :v], map(x->-1*x, df[!, :v]));\n",
    "    q=Quiver(x=X, y=Y, u=U, v=V, vector_scale=0.01, arrow_scale=0.001,  angle=pi/18)\n",
    "    fig = quiverPlot(q;) \n",
    "    update!(fig, line_width=0.75,  [1],  \n",
    "            layout=Layout(width=700, height=500)) \n",
    "    return(fig)\n",
    "end    \n",
    "df = CSV.read(\"quiver.csv\", DataFrame);\n",
    "fig= get_quiver_plot(df);\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "a02a3c12",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "  8.131 ms (123422 allocations: 26.05 MiB)\n"
     ]
    }
   ],
   "source": [
    "@btime get_quiver_plot(df);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1588168a",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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